Stream, path and streak lines are known to be very useful for the visualization
of unsteady flows. Despite their importance in practice, appropriate algorithms
suited for contemporary hardware are rare. In particular, the adaptive
construction of the different line types is not sufficiently studied.

This work provides a profound representation and discussion of stream, path and
streak lines. Two algorithms are proposed for efficiently and accurately
generating these lines using modern graphics hardware. Each includes a scheme
for adaptive time-stepping. The adaptivity for stream and path lines is achieved
through a new processing idea we call selective transform feedback. The
adaptivity for streak lines combines adaptive time-stepping and a geometric
refinement of the curve itself. The approach is evaluated by applying it to
analytically defined and texture-based examples.

Typically, flow volumes are represented and visualized by describing their
boundary as the iso-surface of a level set function. The particle
level set (PLS) method combines the advantages of both grid- and
particle-based level set representations.

This work demonstrates that the PLS method can be adapted to volumetric dye
advection via streak volumes, and to the visualization by time surfaces and path
volumes. This is achieved with a modified and extended PLS, including a model
for dye injection. A new algorithmic interpretation of PLS is introduced in
order to exploit the efficiency of modern graphics hardware, leading to an
interactive visualization. Finally, the high quality and usefulness of PLS flow
visualization is demonstrated by providing quantitative results on volume
preservation and by discussing typical applications of 3D flow visualization.

Direct flow visualizations can help climate researchers to explore flow
characteristics by adjusting parameters and thus controlling the visual output.
They provide an intuitive insight into complex flow data sets such as simulated
circulations of the atmosphere or the ocean. Recent developments in
visualization techniques exploiting programmable features of current graphics
processing units (GPUs) have proven to be very powerful. This is especially true
for particle-based techniques.

This work presents a complete GPU-based particle engine and framework for the
real-time visualization of unsteady climate flow data sets. This involves a
proper data work flow from the simulation back-end to the visualizer, the
handling of non-uniform data grids and, finally, a proper support for the
interactive exploration. We evaluate our framework with a South Asian typhoon
simulated by the DKRZ Hamburg.

The application has been extended to
multi-node
rendering in order to immerse the user into the virtual reality cave at the
University of Siegen. The cave consists of a cylindrical projection area
composed of six (stereo) projectors (four front, two floor). An enhanced
interactivity is achieved by introducing head and object tracking to the user
interface.

Level sets are used for the representation and evolution of closed surfaces.
Grid-based level sets offer a good global representation which deals well with
topological changes, but they suffer from numerical diffusion, whereas
particle-based methods preserve details more accurately but introduce the
problem of unequal global representation. The particle level set (PLS) method
combines the advantages of both approaches by interchanging the information
between the grid and the particles.

This work presents an enhanced PLS approach which fully maps to the GPU.
Improvements w.r.t. the original PLS technique include a sub-voxel interface
representation and an accurate level set correction using more precise particle
radii. Compared to a public CPU-based reference implementation, our method
achieves both, higher performance and superior quality in terms of volume
preservation.

As a concrete application we demonstrate that our fast and accurate PLS is
also well-suited for the visualization of dynamic flows.

The main research approaches in computational fluid dynamics (CFD) are
grid-based or particle-based. For interactive fluid simulations, grid-based
techniques for the use of Graphics Processing Units (GPUs) have been developed
in order to speed up the simulation.

This paper describes an approach for setting up a particle-based fluid
simulation on the GPU. This builds upon earlier results on simulation of
uncoupled particles. The major contribution of this work is a new approach for
modeling dynamic particle coupling solely based on individual particle
contributions. This technique does not need global sorting or an explicit
solution of the n-nearest neighbor problem.